The present disclosure relates generally to receiving motion-identifying signals from a plurality of mobile electronic devices and determining current traffic information based on the motion.
Traffic patterns can exhibit a large degree of unpredictability. For example, vehicle accidents, new construction efforts, weather-based road damage, and road closures can cause direct traffic congestion (e.g., on an affected road) and indirect traffic congestion (e.g., on another road or on a same road with respect to traffic moving in an opposite direction).
At times, a person's traveling patterns can be flexible. For example, the person can commute to a destination along an alternative route, or a person can adjust a departure time. In order to identify whether one such strategy should be implemented, it is useful to identify a status of traffic along potential routes. A person can, e.g., watch a television traffic report prior to his morning commute and determine an initial route. However, the television traffic report may not provide adequate detail with regard to a particular route, or events can soon modify traffic conditions. Once in route, it can be difficult to determine whether to adjust a commute to avoid traffic. A driver can be trapped in deadlock traffic prior to realizing an extent of congestion, or a driver may have missed an exit to his alternative route before realizing a degree of upcoming congestion.
Encounters of high-traffic conditions are likely to frustrate a driver and to reduce the time that the driver can otherwise spend on productive or leisure activities. Additionally, accumulating more vehicles within a congested area can have environmental consequences: vehicles running for longer periods of time and subjected to larger variations in speed can result in increased pollution.